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Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test de racine unitaire ADF avec rupture structurelle× | Test de racine unitaire de Phillips-Perron× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1989-1992 | 1988 |
| Auteur d'origine≠ | Perron (1989); Zivot and Andrews (1992) | Peter C. B. Phillips and Pierre Perron |
| Type≠ | Unit root test with structural break | Hypothesis test (unit root) |
| Source fondatrice≠ | Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57(6), 1361-1401. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| Alias | ADF with structural break, Perron unit root test, break-augmented ADF, unit root test with structural change | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | The structural break ADF unit root test extends the standard Augmented Dickey-Fuller test to allow for one or more discrete shifts in the level or trend of a time series. Because ignoring a structural break inflates the apparent persistence of a series, this test prevents false acceptance of the unit root null when the series is actually stationary around a shifting mean or trend. | The Phillips-Perron (PP) test is a nonparametric unit root test for time series that corrects for serial correlation and heteroscedasticity in the error term without adding lagged differences. Introduced by Phillips and Perron (1988), it applies a kernel-based long-run variance estimator to adjust the Dickey-Fuller statistic, making it robust to a wide class of weakly dependent error processes. |
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